The present invention relates to an air-fuel ratio control system for an engine having a learning control function.
An electronic control fuel injection system (EGI) generally determines an injection quantity by compensating a basic fuel injection quantity T.sub.P by various compensation factors
The basic quantity T.sub.P is the injection quantity to obtain a theoretical air-fuel ratio corresponding to a suction air quantity Q.sub.A and an engine speed S.sub.E and is calculated by: EQU T=K.times.Q.sub.A /S.sub.E
where K is a constant. The actual fuel injection quantity Ti is set by multiplying the basic quantity T.sub.P by various correction coefficients corresponding to various operational conditions of the engine.
The various correction coefficients include various quantities of increase correction coefficient C.sub.I for adapting the air-fuel ratio to the operational condition at the time, an acceleration/deceleration correction coefficient K.sub.S, an air-fuel ratio feedback correction coefficient .alpha. for the theoretical air-fuel ratio, and a voltage correction coefficient T.sub.s. The air-fuel ratio is controlled by the actual fuel injection quantity T.sub.i set by various correction coefficients. Namely, the quantity T.sub.i is set by; EQU T.sub.I =T.sub.P .times..alpha..times.(C.sub.I +K.sub.S)+T.sub.S
In order to keep the air-fuel ratio under the theoretical ratio, an exhaust sensor such as an oxygen sensor exposed in an exhaust pipe, measures oxygen density of exhaust gases and calculates an air-fuel ratio of the induced mixture. Air-fuel ratio feedback control is performed by a compensation amount in dependency on a difference between the calculated air-fuel ratio and the theoretical air-fuel ratio.
However, the air-fuel ratio feedback control requires a long time to set an actual air-fuel ratio equal to a reference air-fuel ratio if the deviation between the reference ratio and disturbance is not within predetermined limits. Furthermore, it is possible for the control of the air-fuel feedback control system to be disabled by instabilities such as overshoot or hunting of the air-fuel ratio when an operation range rapidly changes or when a control output misses the reference in dependency on factors changing with the lapse of time.
Accordingly, more precise air-fuel control is realized by learning control having a learning value of the amount of difference between the air-fuel ratios in order to increase conformity with a control value and the reference, to compensate for inferiority of individual parts or differences between the characteristics of each part, and to precisely correct the air-fuel ratio within regions in which air-fuel ratio feedback control cannot be performed. Namely, if a learning correction coefficient denotes K.sub.L, the fuel injection quantity T.sub.i is calculated by the following equation; EQU T.sub.i =T.sub.P .times..alpha..times.(C.sub.I .times.K.sub.L .times.K.sub.S)+T.sub.S
and the air-fuel ratio is controlled by the fuel injection quantity T.sub.i corrected by learning.
Such air-fuel ratio control by learning is disclosed in, for example, Japanese patent laid-open No. 60-93150 (1985). The prior art corrects an air-fuel ratio not only during the air-fuel ratio feedback control but also in the region where the air-fuel ratio feedback control is not performed. The air-fuel ratio is controlled by correcting the constant K to calculate the fundamental fuel injection quantity T.sub.P corresponding to the difference between a learning correction coefficient and an initial value only when the coefficient is renewed over the predetermined degree and has a difference against the initial value in the same direction. The coefficient is stored in a map on a random access memory (RAM) in dependency on an operational condition for the engine such as the engine speed and an engine load.
However, the map storing the learning correction coefficient requires a large memory capacity. Low learning frequencies in any region lack precision for the control because of the correction by assumption. Since the renewal of the map, i.e. the rewriting of the memory requires a longer time as the memory becomes large, the control procedure is complicated so that the convergency of the learning value deteriorates.
Furthermore, the cause depending on the air-fuel ratio mainly occurs in a measuring system for the suction air quantity such as a suction air quantity sensor and in a fuel injection system such as an injector or pressure regulator. As shown in FIG. 4(c), the deterioration characteristics of the change, lapse with time occurring in the measuring system are different from those in the fuel injection system. Accordingly, a miscalculation of the suction air quantity is caused by the change due to extended use of the measuring system such as the suction air quantity sensor. Furthermore, the miscalculation is different from an error of the actual fuel injection quantity caused by the fuel injection system is correspondence to the operational regions in dependency on the difference of deterioration characteristics of both system. Therefore, the deterioration of the control ability and learning accuracy is a problem because the learning value of one system conflicts with the value of the other system in the same learning region. For example, the correction learning for discrepancy of the air-fuel ratio caused by the deterioration of suction air quantity sensor is different from the correction learning for discrepancies of the air-fuel ratio caused by deterioration occurring in the injector or the pressure regulator.